As soon as a company’s solution to the market problem is validated, it should go after customers that are most likely to buy and discern most value from the company’s offerings and market position – i.e. go after the Sweet Spot
Years ago, a marketing professor in business school analogized the act of segmentation (which is the formal term for this exercise) to finding a life partner. She explained it this way: “find someone [customer] who really appreciates your good qualities and can put up with your bad qualities”. That sums it up well, in theory. In practice, segmentation focuses on the commercialization aspects of a company – who does a company sell to?
Segmentation is a highly analytical exercise of creating a mold from one or two most optimal customer groups, articulated in terms of their observable properties. This mold is the company’s Sweet Spot. The optimal customer groups: 1) are most likely to buy from the company, 2) derive most value from the company’s offerings, and 3) offer a large market opportunity for the company to attack.
The Sweet Spot qualifies customers that the company designs / builds its offerings for, and sells to proactively. It does not mean customers outside the sweet spot won’t buy on their own volition.
Why Is Segmentation Important?
Efficiency, Efficiency, Efficiency. It allows an organization to channel its resources to go after customers that are similar, easiest to sell to, and has the most to gain from the company’s offerings. Once a company knows its market position (i.e. how the company chooses to solve the market problem and what it chooses to be spectacularly good at), the company has to take the time to decide the optimal audience for its offerings from among billions of consumers and millions of companies around the world.
During early stages of existence, companies (founders and early staff) are under pressure to prove their solution to themselves and potential investors. The company also doesn’t have much data to rely on to decide who to sell to. So, it is rational to take a broad commercial approach to test market viability and capture revenue, as very little reliable information is available. In this stage, the customers that buy from the company are early adopters who are risk takers. They are most likely to try new offerings and risk living with some capability gaps. But this is usually a very small portion of the market.
As the company grows and boasts a relevant number of customers and revenue, it is time to fine-tune how the company goes to market. The company’s chosen market position already articulates exactly how the company intends to solve the market problem. Customers (consumers and companies) are different enough that not everyone is equally likely to buy from the company or, even if they buy, unlikely to appreciate the company’s offerings equally well. So, why waste time and resources going after customers who are less likely to buy or become undesirable customers (costs too much to serve or ends up being short-term customers)? There are no good reasons.
Approach To Identify The Sweet Spot
First of all, segmentation is a commonly used “S” word in business parlance and like other “S” words, it is often misused and misunderstood. If we were able to mind-meld (in Star Trek terminology), it would be clear that almost everyone using the word is talking about something slightly different. Although it sounds very basic, the first and most important step is to be absolutely clear among all senior executives and analytical players in a company what segmentation will deliver and how it will be used.
Second, it takes complex qualitative and quantitative assessments to get to a reasonable answer for segmentation. So, this article won’t offer a tutorial on how to do segmentation (maybe over time). Let us start with some guardrails on key deliverables of the exercise that everyone should look for.
1: Universe of customers based on observable characteristics
Whether a company operates in a business-to-business or business-to-consumer environment, existing and potential customers can be described based on externally observable characteristics. Choose a handful of meaningful characteristics, and 2 to 4 categories for each characteristic that every single potential customer can be grouped into. Most importantly, these characteristics and categories differentiate buying needs and behaviors. This is the hardest part of the whole exercise and will take discipline and strong business acumen of how the universe of potential customers operate.
If the customer is an individual consumer, these characteristics describe a human being and their behaviors. Characteristics might include:
- Personal attributes such as age, gender, ethnicity, etc.
- Economic proxies such as employment, neighborhood, property ownership, etc.
- Behavioral traits such as frequent traveller, fitness enthusiast, etc.
- Relationship traits such as parent, married, single, etc.
If the customer is a company, these characteristics together filter down the universe of companies to a small manageable number. Such business traits might include:
- Size of the customer, based on employee count or revenue
- Position in the value chain – does the potential customer sell to companies or consumers? Or is the customer a manufacturer, distributor, or retailer?
- Geographic location by country or other regional categories
- Sector in which the customer operates such as industrials, chemicals, healthcare, etc.
- Does the customer operate in a highly regulated or an unregulated environment?
- Is the customer a service provider or a product seller?
Irrespective of how these traits are defined, pressure test them with the following considerations:
- Every single characteristic used should be unambiguous and non-interpretive. i.e. different individuals should look at potential customers and put them into same categories for all characteristics. e.g. if I categorize a potential customer as a ‘distributor’, my colleagues should categorize that customer the same way, for the value chain characteristic. Ambiguous characteristics or underlying choices will lead to misleading takeaways.
- Somewhat accurate information has to be available for every single characteristic and available from an objective data provider (or gathered reliably internally)
What does a good deliverable look like? Say, a company identifies four specific characteristics [one example could be size of customer], and each characteristic has two categories [e.g. large customers with revenue > $1B OR small customers with revenue <$1B]; then, the universe of all potential customers should fit into eight groups [4 characteristics * 2 categories each].
2: Ranked customer groups
If step 1 is coming up with the X-axis, step 2 is calculating the data points for the Y-axis. In English, we have to take the customer groups in step 1 and figure out which are the best one or two groups.
Frankly, this is not a trivial exercise and require serious analytical muscles and experience to execute. The company will need a strong objective & analytical culture as a foundation, and should rely on strong analytical players for this exercise. So, we won’t cover the analytical details that go into ranking customer groups here. But the following considerations must be part of that assessment and visible to everyone in the company. As an output of this step, look for how various customer groups stack up against each other along the following dimensions:
- Probability of buying from the company, given the chosen market position
- Likely longevity of each customer group’s loyalty
- Value derived by the customer group (points to company’s pricing power)
- Market opportunity presented by each customer group
3: The Sweet Spot
If the first two steps are done well, step 3 is easy. All we are doing here is taking the top one or two customer groups from step 2 and framing their common properties as the Sweet Spot.
As a hypothetical example, a high-end scented candle producer can think about many applications for its products and many paths to sell. But a careful segmentation exercise can result in a sweet spot as shown below.
- Illustrative sweet spot for a high-end scented candle producer (in practice, the output will have significantly more substantiation and qualification)
- Small companies (less than 100 employees)
- Independently owned (not a franchise or part of larger corporation)
- Selling to customers directly
- Operating in a physical retail space
- In a city with population >500,000
- In business for less than 5 years
Such an articulation of the Sweet Spot allows the company to tailor its product and commercial strategy, including number and type of SKUs to design and manufacture, approach to distribute products, and several other sales and marketing decisions.
Two Common Mistakes
Identifying the Sweet Spot is a complex exercise and can result in suboptimal lessons, unless common pitfalls are avoided.
Pitfall 1: Trying to use one major characteristic as the Sweet Spot. For example, Sector is a major characteristic; but using it as the only characteristic is an erroneous approach. If a company chooses Auto sector as its Sweet Spot, it would try to build offerings for and sell to all Auto companies. But Auto has a very broad set of companies with very different needs. The company will disappoint many Auto customers and miss out on companies in other sectors that would have fit well into its Sweet Spot.
Pitfall 2: Using many characteristics in an elaborate polynomial equation to come up with an optimal customer score and stopping there. The Sweet Spot is not a list of top target companies. It is a fine-tuned articulation of likely customers that a company can use to develop its product and commercial strategy around.
To conclude, investing time and mindshare to identify a company’s Sweet Spot is critical to effectively and efficiently deploy product and commercial resources. It simplifies the company’s approach to attack the market and gives every function and employee a clear and cohesive view of the properties of an ideal customer.